Terrorism Risks and Cost‐Benefit Analysis of Aviation Security

We evaluate, for the U.S. case, the costs and benefits of three security measures designed to reduce the likelihood of a direct replication of the 9/11 terrorist attacks. To do so, we assess risk reduction, losses, and security costs in the context of the full set of security layers. The three measures evaluated are installed physical secondary barriers (IPSB) to restrict access to the hardened cockpit door during door transitions, the Federal Air Marshal Service (FAMS), and the Federal Flight Deck Officer (FFDO) Program. In the process, we examine an alternate policy measure: doubling the budget of the FFDO program to $44 million per year, installing IPSBs in all U.S. aircraft at a cost of $13.5 million per year, and reducing funding for FAMS by 75% to $300 million per year. A break‐even cost‐benefit analysis then finds the minimum probability of an otherwise successful attack required for the benefit of each security measures to equal its cost. We find that the IPSB is costeffective if the annual attack probability of an otherwise successful attack exceeds 0.5% or one attack every 200 years. The FFDO program is costeffective if the annual attack probability exceeds 2%. On the other hand, more than two otherwise successful attacks per year are required for FAMS to be costeffective. A policy that includes IPSBs, an increased budget for FFDOs, and a reduced budget for FAMS may be a viable policy alternative, potentially saving hundreds of millions of dollars per year with consequences for security that are, at most, negligible.     

Cost‐Benefit Analysis of Passive Fire Protections in Road LPG Transportation

The cost‐benefit evaluation of passive fire protection adoption in the road transport of liquefied petroleum gas (LPG) was investigated. In a previous study, mathematical simulations of real scale fire scenarios proved the effectiveness of passive fire protections in preventing the “fired” boiling liquid expanding vapor explosion (BLEVE), thus providing a significant risk reduction. In the present study the economical aspects of the adoption of fire protections are analyzed and an approach to cost‐benefit analysis (CBA) is proposed. The CBA model is based on the comparison of the risk reduction due to fire protections (expressed in monetary terms by the value of a statistical life) and the cost of the application of fire protections to a fleet of tankers. Different types of fire protections were considered, as well as the possibility to apply protections to the entire fleet or only to a part of it. The application of the proposed model to a real‐life case study is presented and discussed. Results demonstrate that the adoption of passive fire protections on road tankers, though not compulsory in Europe, can be economically feasible, thus representing a concrete measure to achieve control of the “major hazard accidents” cited by the European legislation.     

Benefit Analysis for Natural Hazards

The objective of this paper is to develop the ex ante perspective for benefit analysis with natural hazards. It defines an ex ante evaluation of the economic benefits that arise from policies designed to reduce either the risk of or the detrimental effects associated with a natural hazard. In the process the paper compares the ex ante and ex post perspectives and discusses the prospects for implementing the framework by measuring the valuation concepts that are developed.     

Risk‐Cost‐Benefit Analysis for Transportation Corridors with Interval Uncertainties of Heterogeneous Data

Access management, which systematically limits opportunities for egress and ingress of vehicles to highway lanes, is critical to protect trillions of dollars of current investment in transportation. This article addresses allocating resources for access management with incomplete and partially relevant data on crash rates, travel speeds, and other factors. While access management can be effective to avoid crashes, reduce travel times, and increase route capacities, the literature suggests a need for performance metrics to guide investments in resource allocation across large corridor networks and several time horizons. In this article, we describe a quantitative decision model to support an access management program via risk‐cost‐benefit analysis under data uncertainties from diverse sources of data and expertise. The approach quantifies potential benefits, including safety improvement and travel time savings, and costs of access management through functional relationships of input parameters including crash rates, corridor access point densities, and traffic volumes. Parameter uncertainties, which vary across locales and experts, are addressed via numerical interval analyses. This approach is demonstrated at several geographic scales across 7,000 kilometers of highways in a geographic region and several subregions. The demonstration prioritizes route segments that would benefit from risk management, including (i) additional data or elicitation, (ii) right‐of‐way purchases, (iii) restriction or closing of access points, (iv) new alignments, (v) developer proffers, and (vi) etc. The approach ought to be of wide interest to analysts, planners, policymakers, and stakeholders who rely on heterogeneous data and expertise for risk management.     

Cost‐Effective Application of Thermal Protection on LPG Road Transport Tanks for Risk Reduction Due to Hot BLEVE Incidents

A simplified risk and cost‐benefit analysis is presented for the application of thermal protection (TP) on propane and LPG highway tanker trucks operating in North America. A risk analysis is performed to determine the benefits of risk reduction by TP, relative to the costs of applying and maintaining TP on a tanker truck. The results show that TP is cost effective if the tanker truck spends enough time (or travels enough distance) in areas of moderate or high population density. The analysis is very sensitive to a number of inputs, including: (i) value of life, (ii) hot boiling liquid expanding vapor explosion frequency, (iii) public exposure to severe hazards, and (iv) life cost of TP. With this simplified analysis, it is possible to generate tanker truck exposure times to the public that justify the application of TP based on cost and benefit considerations.     

Application of Graph Theory to Cost‐Effective Fire Protection of Chemical Plants During Domino Effects

In the present study, we have introduced a methodology based on graph theory and multicriteria decision analysis for cost‐effective fire protection of chemical plants subject to fire‐induced domino effects. By modeling domino effects in chemical plants as a directed graph, the graph centrality measures such as out‐closeness and betweenness scores can be used to identify the installations playing a key role in initiating and propagating potential domino effects. It is demonstrated that active fire protection of installations with the highest out‐closeness score and passive fire protection of installations with the highest betweenness score are the most effective strategies for reducing the vulnerability of chemical plants to fire‐induced domino effects. We have employed a dynamic graph analysis to investigate the impact of both the availability and the degradation of fire protection measures over time on the vulnerability of chemical plants. The results obtained from the graph analysis can further be prioritized using multicriteria decision analysis techniques such as the method of reference point to find the most cost‐effective fire protection strategy.     

Reducing the Risk of Injury from Table Saw Use: The Potential Benefits and Costs of Automatic Protection

The use of table saws in the United States is associated with approximately 28,000 emergency department (ED) visits and 2,000 cases of finger amputation per year. This article provides a quantitative estimate of the economic benefits of automatic protection systems that could be designed into new table saw products. Benefits are defined as reduced health‐care costs, enhanced production at work, and diminished pain and suffering. The present value of the benefits of automatic protection over the life of the table saw are interpreted as the switch‐point cost value, the maximum investment in automatic protection that can be justified by benefit‐cost comparison. Using two alternative methods for monetizing pain and suffering, the study finds switch‐point cost values of $753 and $561 per saw. These point estimates are sensitive to the values of inputs, especially the average cost of injury. The various switch‐point cost values are substantially higher than rough estimates of the incremental cost of automatic protection systems. Uncertainties and future research needs are discussed.     

A Comprehensive Risk Analysis of Transportation Networks Affected by Rainfall‐Induced Multihazards

Climate change and its projected natural hazards have an adverse impact on the functionality and operation of transportation infrastructure systems. This study presents a comprehensive framework to analyze the risk to transportation infrastructure networks that are affected by natural hazards. The proposed risk analysis method considers both the failure probability of infrastructure components and the expected infrastructure network efficiency and capacity loss due to component failure. This comprehensive approach facilitates the identification of high‐risk network links in terms of not only their susceptibility to natural hazards but also their overall impact on the network. The Chinese national rail system and its exposure to rainfall‐related multihazards are used as a case study. The importance of various links is comprehensively assessed from the perspectives of topological, efficiency, and capacity criticality. Risk maps of the national railway system are generated, which can guide decisive action regarding investments in preventative and adaptive measures to reduce risk.     

A Tiered Approach for Risk‐Benefit Assessment of Foods

Risk‐benefit analyses are introduced as a new paradigm for old problems. However, in many cases it is not always necessary to perform a full comprehensive and expensive quantitative risk‐benefit assessment to solve the problem, nor is it always possible, given the lack of required date. The choice to continue from a more qualitative to a full quantitative risk‐benefit assessment can be made using a tiered approach. In this article, this tiered approach for risk‐benefit assessment will be addressed using a decision tree. The tiered approach described uses the same four steps as the risk assessment paradigm: hazard and benefit identification, hazard and benefit characterization, exposure assessment, and risk‐benefit characterization, albeit in a different order. For the purpose of this approach, the exposure assessment has been moved upward and the dose‐response modeling (part of hazard and benefit characterization) is moved to a later stage. The decision tree includes several stop moments, depending on the situation where the gathered information is sufficient to answer the initial risk‐benefit question. The approach has been tested for two food ingredients. The decision tree presented in this article is useful to assist on a case‐by‐case basis a risk‐benefit assessor and policymaker in making informed choices when to stop or continue with a risk‐benefit assessment.     

Risk Analysis for Critical Asset Protection

This article proposes a quantitative risk assessment and management framework that supports strategic asset-level resource allocation decision making for critical infrastructure and key resource protection. The proposed framework consists of five phases: scenario identification, consequence and criticality assessment, security vulnerability assessment, threat likelihood assessment, and benefit-cost analysis. Key innovations in this methodology include its initial focus on fundamental asset characteristics to generate an exhaustive set of plausible threat scenarios based on a target susceptibility matrix (which we refer to as asset-driven analysis) and an approach to threat likelihood assessment that captures adversary tendencies to shift their preferences in response to security investments based on the expected utilities of alternative attack profiles assessed from the adversary perspective. A notional example is provided to demonstrate an application of the proposed framework. Extensions of this model to support strategic portfolio-level analysis and tactical risk analysis are suggested.     

Decision Making for Animal Health and Welfare: Integrating Risk‐Benefit Analysis with Prospect Theory

This study integrated risk‐benefit analysis with prospect theory with the overall objective of identifying the type of management behavior represented by farmers’ choices of mastitis control options (MCOs). Two exploratory factor analyses, based on 163 and 175 Swedish farmers, respectively, highlighted attitudes to MCOs related to: (1) grouping cows and applying milking order to prevent spread of existing infection and (2) working in a precautionary way to prevent mastitis occurring. This was interpreted as being based on (1) reactive management behavior on detection of udder‐health problems in individual cows and (2) proactive management behavior to prevent mastitis developing. Farmers’ assessments of these MCOs were found to be based on asymmetrical evaluations of risks and benefits, suggesting that farmers’ management behavior depends on their individual reference point. In particular, attitudes to MCOs related to grouping cows and applying milking order to prevent the spread of mastitis once infected cows were detected were stronger in the risk domain than in the benefit domain, in accordance with loss aversion. In contrast, attitudes to MCOs related to working in a precautionary way to prevent cows from becoming infected in the first place were stronger in the benefit domain than in the risk domain, in accordance with reverse loss aversion. These findings are of practical importance for farmers and agribusiness and in public health protection work to reduce the current extensive use of antibiotics in dairy herds.     

What Affects the Quality of Economic Analysis for Life‐Saving Investments?‡

Economic analysis of life-saving investments in both the public and private sectors has the potential to dramatically improve longevity and the quality of life, but only if the analyses on which decisions are based are done well. In this article, we analyze a data set that provides information on the content and quality of journal articles that measure the cost-effectiveness of life-saving investments. Our study is the first to provide a detailed multivariate analysis of factors affecting objective measures of quality. We also explore whether a series of recommendations by an expert panel convened by the U.S. Public Health Service affect the way analyses of specific life-saving investments are done. Our results suggest that four factors are positively correlated with an index we construct to measure analytical quality: (1) having at least one author affiliated with a university, (2) publication in a journal that has experience in publishing these analyses, (3) if the life-saving investment is located in the United States, and (4) if the analysis considers a measure of social costs or benefits. Somewhat surprisingly, a study's funding source and whether it is affiliated with industry are not significantly correlated with the quality index. Finally, neither time nor the panel guidelines had an impact on the index.     

Risk Mapping of Groundwater‐Drawdown‐Induced Land Subsidence in Heterogeneous Soils on Large Areas

Groundwater leakage into subsurface constructions can cause reduction of pore pressure and subsidence in clay deposits, even at large distances from the location of the construction. The potential cost of damage is substantial, particularly in urban areas. The large‐scale process also implies heterogeneous soil conditions that cannot be described in complete detail, which causes a need for estimating uncertainty of subsidence with probabilistic methods. In this study, the risk for subsidence is estimated by coupling two probabilistic models, a geostatistics‐based soil stratification model with a subsidence model. Statistical analyses of stratification and soil properties are inputs into the models. The results include spatially explicit probabilistic estimates of subsidence magnitude and sensitivities of included model parameters. From these, areas with significant risk for subsidence are distinguished from low‐risk areas. The efficiency and usefulness of this modeling approach as a tool for communication to stakeholders, decision support for prioritization of risk‐reducing measures, and identification of the need for further investigations and monitoring are demonstrated with a case study of a planned tunnel in Stockholm.     

Ecological Risk – Benefit Analysis of a Wetland Development Based on Risk Assessment Using Expected Loss of Biodiversity

Ecological risk from the development of a wetland is assessed quantitatively by means of a new risk measure, expected loss of biodiversity (ELB). ELB is defined as the weighted sum of the increments in the probabilities of extinction of the species living in the wetland due to its loss. The weighting for a particular species is calculated according to the length of the branch on the phylogenetic tree that will be lost if the species becomes extinct. The length of the branch on the phylogenetic tree is regarded as reflecting the extent of contribution of the species to the taxonomic diversity of the world of living things. The increments in the probabilities of extinction are calculated by a simulation used for making the Red List for vascular plants in Japan. The resulting ELB for the loss of Nakaikemi wetland is 9,200 years. This result is combined with the economic costs for conservation of the wetland to produce a value for the indicator of the cost per unit of biodiversity saved. Depending on the scenario, the value is 13,000 yen per year-ELB or 110,000 to 420,000 yen per year-ELB (1 US dollar = 110 yen in 1999).     

Science for Policy: A Case Study of Scientific Polarization,Values, and the Framing of Risk and Uncertainty

It is well documented that more research can lead to hardened positions, particularly when dealing with complex, controversial, and value‐laden issues. This study is an attempt to unveil underlying values in a contemporary debate, where both sides use scientific evidence to support their argument. We analyze the problem framing, vocabulary, interpretation of evidence, and policy recommendations, with particular attention to the framing of nature and technology. We find clear differences between the two arguments. One side stress that there is no evidence that the present approach is causing harm to humans or the environment, does not ruminate on uncertainties to that end, references nature's ability to handle the problem, and indicates distrust in technological solutions. In contrast, the other side focuses on uncertainties, particularly the lack of knowledge about potential environmental effects and signals trust in technological development and human intervention as the solution. Our study suggests that the two sides’ diverging interpretations are tied to their perception of nature: vulnerable to human activities versus robust and able to handle human impacts. The two sides also seem to hold diverging views of technology, but there are indications that this might be rooted in their perception of governance and economy rather than about technology per se. We conclude that there is a need to further investigate how scientific arguments are related to worldviews, to see how (if at all) worldview typologies can help us to understand how value‐based judgments are embedded in science advice, and the impact these have on policy preferences.     

Confronting Deep Uncertainties in Risk Analysis

How can risk analysts help to improve policy and decision making when the correct probabilistic relation between alternative acts and their probable consequences is unknown? This practical challenge of risk management with model uncertainty arises in problems from preparing for climate change to managing emerging diseases to operating complex and hazardous facilities safely. We review constructive methods for robust and adaptive risk analysis under deep uncertainty. These methods are not yet as familiar to many risk analysts as older statistical and model‐based methods, such as the paradigm of identifying a single “best‐fitting” model and performing sensitivity analyses for its conclusions. They provide genuine breakthroughs for improving predictions and decisions when the correct model is highly uncertain. We demonstrate their potential by summarizing a variety of practical risk management applications.     

Cultural Values,Trust, and Benefit‐Risk Perceptions of Hydraulic Fracturing: A Comparative Analysis of Policy Elites and the General Public

Hydraulic fracturing (“fracking”) has recently become a very intensely debated process for extracting oil and gas. Supporters argue that fracking provides positive economic benefits and energy security and offers a decreased reliance on coal‐based electricity generation. Detractors claim that the fracking process may harm the environment as well as place a strain on local communities that experience new fracking operations. This study utilizes a recently conducted survey distributed to a sample of policy elites and the general public in Arkansas and Oregon to examine the role of cultural value predispositions and trust in shaping the perceptions of risks and benefits associated with fracking. Findings indicate that cultural values influence both trust and benefit‐risk perceptions of fracking for both policy elites and the general public. More specifically, we found that trust in information from various sources is derived from the intrinsic values held by an individual, which in turn impacts perceptions of related benefits and risks. We also found that while the overall pattern of relationships is similar, trust plays a larger role in the formulation of attitudes for policy elites than for the general public. We discuss the implications of the mediating role of trust in understanding value‐driven benefit‐risk perceptions, as well as the disparate role of trust between policy elites and the general public in the context of the policy‐making process for both theory and practice.     

Modeling the Cost Effectiveness of Fire Protection Resource Allocation in the United States: Models and a 1980–2014 Case Study

The estimated cost of fire in the United States is about $329 billion a year, yet there are gaps in the literature to measure the effectiveness of investment and to allocate resources optimally in fire protection. This article fills these gaps by creating data‐driven empirical and theoretical models to study the effectiveness of nationwide fire protection investment in reducing economic and human losses. The regression between investment and loss vulnerability shows high R² values (≈0.93). This article also contributes to the literature by modeling strategic (national‐level or state‐level) resource allocation (RA) for fire protection with equity‐efficiency trade‐off considerations, while existing literature focuses on operational‐level RA. This model and its numerical analyses provide techniques and insights to aid the strategic decision‐making process. The results from this model are used to calculate fire risk scores for various geographic regions, which can be used as an indicator of fire risk. A case study of federal fire grant allocation is used to validate and show the utility of the optimal RA model. The results also identify potential underinvestment and overinvestment in fire protection in certain regions. This article presents scenarios in which the model presented outperforms the existing RA scheme, when compared in terms of the correlation of resources allocated with actual number of fire incidents. This article provides some novel insights to policymakers and analysts in fire protection and safety that would help in mitigating economic costs and saving lives.     

A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.     

Some Limitations of “Risk = Threat × Vulnerability × Consequence” for Risk Analysis of Terrorist Attacks

Several important risk analysis methods now used in setting priorities for protecting U.S. infrastructures against terrorist attacks are based on the formula: Risk=Threat×Vulnerability×Consequence. This article identifies potential limitations in such methods that can undermine their ability to guide resource allocations to effectively optimize risk reductions. After considering specific examples for the Risk Analysis and Management for Critical Asset Protection (RAMCAP?) framework used by the Department of Homeland Security, we address more fundamental limitations of the product formula. These include its failure to adjust for correlations among its components, nonadditivity of risks estimated using the formula, inability to use risk‐scoring results to optimally allocate defensive resources, and intrinsic subjectivity and ambiguity of Threat, Vulnerability, and Consequence numbers. Trying to directly assess probabilities for the actions of intelligent antagonists instead of modeling how they adaptively pursue their goals in light of available information and experience can produce ambiguous or mistaken risk estimates. Recent work demonstrates that two‐level (or few‐level) hierarchical optimization models can provide a useful alternative to Risk=Threat×Vulnerability×Consequence scoring rules, and also to probabilistic risk assessment (PRA) techniques that ignore rational planning and adaptation. In such two‐level optimization models, defender predicts attacker's best response to defender's own actions, and then chooses his or her own actions taking into account these best responses. Such models appear valuable as practical approaches to antiterrorism risk analysis.